Automatic Blurring based on Structural Similarity of Image Detail
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Abstract
Image smoothing is used for a variety of purposes such as removing noise, feeling enhancement, drawing attention to the object. Since the images have different details, they require an appropriate blur level for their contents and applications. Therefore, this research studies and develops automatic blurring method to increase depth impression of image. The blur levels are divided into large blur (very shallow depth of field) and small blur (preserve image structure). The method applies image quality assessment of structural similarity index (SSIM) to measure blur level between images. Only the SSIM values of image detail which affects the blur perception of human are used to compare with the values of appropriate blur levels from preliminary experiment of 100 images. The technique isolates the detail of image in SSIM map by using Otsu’s thresholding method. With the proposed approach, blurred images of both levels can be automatically created to enhance the focus to the key subject of image. The evaluation result from photography expert reveals that the proposed method can assist well in creating dimension of image, time saving of image editing especially for those who are not skilled in art.
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